Quantitative analysis of the murine lipid droplet-associated proteome during diet-induced hepatic steatosis.
|
| Abstract |
Hepatic steatosis is characterized by the accumulation of lipid droplets (LDs), which are composed of a neutral lipid core surrounded by a phospholipid monolayer embedded with many proteins. Although the LD-associated proteome has been investigated in multiple tissues and organisms, the dynamic changes in the murine LD-associated proteome in response to obesity and hepatic steatosis have not been studied. We characterized the hepatic LD-associated proteome of C57BL/6J male mouse livers following high-fat feeding using isobaric tagging for relative and absolute quantification. Of the 1,520 proteins identified with a 5% local false discovery rate, we report a total of 48 proteins that were increased and 52 proteins that were decreased on LDs in response to high-fat feeding. Most notably, ribosomal and endoplasmic reticulum proteins were increased and extracellular and cytosolic proteins were decreased in response to high-fat feeding. Additionally, many proteins involved in fatty acid catabolism or xenobiotic metabolism were enriched in the LD fraction following high-fat feeding. In contrast, proteins involved in glucose metabolism and liver X receptor or retinoid X receptor activation were decreased on LDs of high-fat-fed mice. This study provides insights into unique biological functions of hepatic LDs under normal and steatotic conditions.
|
|---|---|
| Authors | Salmaan Ahmed Khan, Edith E Wollaston-Hayden, Todd W Markowski, LeeAnn Higgins, Douglas G Mashek |
| Journal | Journal of lipid research (J Lipid Res) Vol. 56 Issue 12 Pg. 2260-72 (Dec 2015) ISSN: 1539-7262 [Electronic] United States |
| PMID | 26416795 (Publication Type: Journal Article, Research Support, N.I.H., Extramural) |
| Copyright | Copyright © 2015 by the American Society for Biochemistry and Molecular Biology, Inc. |
| Chemical References |
|
| Topics |
|
Join CureHunter, for free Research Interface BASIC access!
Realize the full power of the drug-disease research graph!